Building of a hierarchy of wines based on terroirs: an initiative from the producers of Muscadet

Spatial variability of vine productivity in winegrapes is important to characterise as both yield and quality are relevant for the production of different wine styles and products. The objectives were to understand how patterns of variability of Cabernet Sauvignon fruit composition changed over time and space, how these patterns could be characterised with indirect measurements, and how spatial patterns of the variation in fruit compositional attributes can aid in improving management. Prior to the 2017 vintage, 125 data vines were distributed across each of four vineyards in the Lodi American Viticultural Area (AVA) of California. Each data vine was sampled at commercial harvest in 2017, 2018, and 2019. Yield components and fruit composition were measured at harvest for each data vine, and maps of yield and fruit composition were produced for eight ‘objective measures of fruit quality’: total anthocyanins, polymeric tannins, quercetin glycosides, malic acid, yeast assimilable nitrogen, β-damascenone, C6 alcohols and aldehydes, and 3-isobutyl-2-methoxypyrazine. Patterns of variation in anthocyanins and phenolic compounds were found to be most stable over time. Given this relative stability, management decisions focused on fruit quality could be based on zonal descriptions of anthocyanins or phenolics to increase profitability in some vineyards. In each vineyard, dormant season pruning weights and soil cores were collected at each location, elevation and soil apparent electrical conductivity surveys were completed, and remotely sensed imagery was captured by fixed wing aircraft and two satellite platforms at major phenological stages. The data collected were used to develop relationships among biophysical data, soil, imagery, and fruit composition. The standardised and aggregated samples from four vineyards over three seasons were included in the estimation of ‘common variograms’ to assess how this technique could aid growers in producing geostatistically rigorous maps of fruit composition variability without cumbersome, single season sampling efforts.

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

Barolo DOCG is an economically important wine producing region in Northwest Italy. It is a small region of approximately 70 km2 gross area. The topography is very complex with steep sloped hills ranging in elevation from below 200 m to 550 m. Barolo DOCG wine is made exclusively from the Nebbiolo grape. Bioclimatic indexes are often used in viticulture to gain a better understanding of broader climate trends which can be compared temporally and geographically. These indexes are also used for identifying potential phenological timing, growing region suitability, and potential risks associated with expected climatic changes. Understanding how topography influences bioclimatic indexes can help with understanding of mesoscale climate behaviour leading to improved decision making and risk management strategies. The average monthly maximum and minimum temperatures, the Cool Night Index, the Huglin Index, and the monthly diurnal range (from July to October) were calculated using data from 45 weather stations within a 40 km radius of the Barolo DOCG growing area between the years 1996 and 2019. Linear and multiple regression models were developed using independent variables (elevation, aspect, slope) extracted from a digital elevation model to identify significant relationships. Bioclimatic indexes were then kriged with external drift using independent variables that showed significant relationships with the bioclimatic index using a 100 m resolution grid. The maximum monthly temperatures and the Huglin Index showed consistent significant negative relationships with elevation in all years. The minimum monthly temperatures showed no relationship with elevation but in some months a small but significant relationship was observed with aspect. Due to the lack of a relationship between minimum monthly temperatures and elevation compared to the significant relationship between maximum monthly temperatures and elevation, monthly diurnal range had a negative relationship with elevation.

The Fruška Gora mountain is a traditional wine-growing region in Serbia situated in the Pannonian Basin. Due to such a position, the vicinity of the Danube River and the presence of concave configuration, it is suitable for grape production. This paper provides analyses of spatial variations in meteorological parameters and grape juice quality within Fruška Gora wine region over three consecutive vintages (2018-2020). The examined period can be defined as warm with cool nights during September (AVG 18,9°C; GDD 1918°C; CI 12°CF) and with the presence of mesoclimatic variability. The East part of the study area was somewhat drier and hotter compared to other parts of the region. The analyses of grape must samples (190 in total) of five cultivars (Cabernet-Sauvignon, Merlot, Chardonnay, Sauvignon blanc and Grašac (Welschriesling)) commonly grown across the region (19 sites), were performed using Fourier Transform Infrared Technology (FTIR). Among all cultivars, Sauvignon blanc was harvested first in the East area (DOY=246±5, GDD at harvest=1552±74, 22.2±0.7 °Brix), while the latest harvest was recorded for Cabernet-Sauvignon in the West (DOY=283±5, GDD at harvest=1936±187, 23.4±1.0 °Brix ). Both the red and white cultivars had higher acidity and YAN in the grape must if the vines were grown in the North and East compared to South and West areas. According to PCA analysis, Grašac showed the lowest variation in grape must chemical composition. Thus, the results confirm that Grašac is the most stable cultivar in Fruška Gora. All monitored cultivars reached technological fruit ripeness by the end of the growing season. However, it was difficult to reach full ripeness of red cultivars, mostly beacuse of uncoupling of technolocical and phenolic ripeness. Thus, Cabernet-Sauvignon had higher variations in GDD sums at harvest compared to other cultivars, which probably increased variations in grape must quality.

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